This Tavily Search MCP server, developed by Alexandros Pappas, integrates the Tavily Search API into the Model Context Protocol framework. Built with TypeScript and leveraging Express.js, it provides a streamlined interface for AI models to perform web searches using Tavily's advanced search capabilities. The implementation supports both stdio and Server-Sent Events (SSE) communication methods, making it versatile for different deployment scenarios. It's particularly useful for enhancing AI-driven applications with real-time, high-quality web search results, enabling use cases like fact-checking, research assistance, or content generation that requires up-to-date information from the internet.
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Execute web searches using the Tavily Search API. Inputs: query (string, required), search_depth (string, optional), topic (string, optional), days (number, optional), time_range (string, optional), max_results (number, optional), include_images (boolean, optional), include_image_descriptions (boolean, optional), include_answer (boolean, optional), include_raw_content (boolean, optional), include_domains (string[], optional), exclude_domains (string[], optional).